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Record W2491402517 · doi:10.1190/1.9781560802197.ch9

Introduction to Geophysical Imaging

2010· book-chapter· en· W2491402517 on OpenAlex
Eleanor C. Willoughby, Michael Riedel, Satinder Chopra

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSociety of Exploration Geophysicists eBooks · 2010
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of TorontoGeological Survey of CanadaNatural Resources Canada
Fundersnot available
KeywordsLibrary scienceGeological surveyColumbia universityGeographyMedia studiesGeologySociologyGeophysicsComputer science

Abstract

fetched live from OpenAlex

As we have seen from the preceeding chapters, it has become widely accepted that straightforward gas-hydrate assessment remains an outstanding issue. Researchers no longer attempt to gauge marine gas-hydrate concentrations from seismic reflectivity maps of the bottom-simulating reflections (BSRs), and rarely can a land-based equivalent to a marine BSR be clearly identified because of the geologic complexity of the permafrost gas-hydrate environment. In fact, there is increasing evidence that gas-hydrate deposits in the marine environment are very heterogeneous in nature, especially from the last major scientific drilling expeditions (e.g., Integrated Ocean Drilling Program Expedition 311, Riedel et al., 2006; India National Gas Hydrate Expedition 01, Collett et al., 2008). Considerable strides have been made to develop more sophisticated geophysical experimental methodologies, inversions, and gas-hydrate assessment methods. The need to employ other geophysical imaging techniques has become more and more evident.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.655
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.212
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it